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Learning scientific programming with Python /
"Learn to master basic programming tasks from scratch with real-life, scientifically relevant examples and solutions drawn from both science and engineering. Students and researchers at all levels are increasingly turning to the powerful Python programming language as an alternative to commerci...
| Autor principal: | |
|---|---|
| Formato: | Printed Book |
| Lenguaje: | English |
| Edición: | Second edition. |
| Materias: |
| LEADER | 02535cam a22003738i 4500 | ||
|---|---|---|---|
| 001 | 21514043 | ||
| 003 | inmpuc | ||
| 005 | 20200917112913.0 | ||
| 006 | m |o d | | ||
| 007 | cr_||||||||||| | ||
| 008 | 200422s2020 nyu ob 001 0 eng | ||
| 010 | |a 2020017918 | ||
| 020 | |a 9781108778039 |q (epub) | ||
| 020 | |z 9781108745918 |q (paperback) | ||
| 040 | |a DLC |b eng |c DLC |e rda | ||
| 042 | |a pcc | ||
| 050 | 0 | 0 | |a Q183.9 |
| 082 | 0 | 0 | |a 005.13/3 |2 23 |
| 100 | 1 | |a Hill, Christian, |d 1974- |e author. | |
| 245 | 1 | 0 | |a Learning scientific programming with Python / |c Christian Hill. |
| 250 | |a Second edition. | ||
| 263 | |a 2010 | ||
| 300 | |a 1 online resource | ||
| 504 | |a Includes bibliographical references and index. | ||
| 520 | |a "Learn to master basic programming tasks from scratch with real-life, scientifically relevant examples and solutions drawn from both science and engineering. Students and researchers at all levels are increasingly turning to the powerful Python programming language as an alternative to commercial packages and this fast-paced introduction moves from the basics to advanced concepts in one complete volume, enabling readers to gain proficiency quickly. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and moving on to the NumPy, SciPy and Matplotlib libraries for numerical programming and data visualization, this textbook also discusses the use of Jupyter Notebooks to build rich-media, shareable documents for scientific analysis. The second edition features a new chapter on data analysis with the pandas library and comprehensive updates, and new exercises and examples. A final chapter introduces more advanced topics such as floating-point precision and algorithm stability, and extensive online resources support further study. This textbook represents a targeted package for students requiring a solid foundation in Python programming"-- | ||
| 650 | 0 | |a Science |x Data processing. | |
| 650 | 0 | |a Science |x Mathematics. | |
| 650 | 0 | |a Python (Computer program language) | |
| 776 | 0 | 8 | |i Print version: |a Hill, Christian, 1974- |t Learning scientific programming with Python |b Second edition. |d New York : Cambridge University Press, 2020. |z 9781108745918 |w (DLC) 2020017917 |
| 906 | |a 7 |b cbc |c orignew |d 1 |e ecip |f 20 |g y-gencatlg | ||
| 942 | |2 ddc |c BK | ||
| 955 | |a ecip ebook 2020-04-28 | ||
| 999 | |c 352784 |d 352784 | ||
| 952 | |0 0 |1 0 |2 ddc |4 0 |6 005_133000000000000_HIL_L |7 0 |9 407782 |a DCS |b DCS |d 2019-08-26 |l 0 |o 005.133 HIL/L |p DCS1572 |r 2020-09-17 |w 2020-09-17 |y BK | ||